title: Towards automatic detection of abnormal retinal capillaries in ultra-widefield-of-view retinal angiographic exams.
abstract: Retinal capillary abnormalities include small, leaky, severely tortuous blood vessels that are associated with a variety of retinal pathologies. We present a prototype image-processing system for detecting abnormal retinal capillary regions in ultra-widefield-of-view (UWFOV) fluorescein angiography exams of the human retina. The algorithm takes as input an UWFOV FA frame and returns the candidate regions identified. An SVM classifier is trained on regions traced by expert ophthalmologists. Tests with a variety of feature sets indicate that edge features and allied properties differentiate best between normal and abnormal retinal capillary regions. Experiments with an initial set of images from patients showing branch retinal vein occlusion (BRVO) indicate promising area under the ROC curve of 0.950 and a weighted Cohen's Kappa value of 0.822.
authors.forename: K
authors.initials: K
authors.lastname: Zutis
authors.forename: E
authors.initials: E
authors.lastname: Trucco
authors.forename: J P
authors.initials: JP
authors.lastname: Hubschman
authors.forename: D
authors.initials: D
authors.lastname: Reed
authors.forename: S
authors.initials: S
authors.lastname: Shah
authors.forename: J
authors.initials: J
authors.lastname: van Hemert
mesh_terms: D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D001330:Electronic Data Processing; D005451:Fluorescein Angiography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D009885:Ophthalmology / Q000295:instrumentation / Q000379:methods; D012372:ROC Curve; D012160:Retina / Q000473:pathology; D012170:Retinal Vein Occlusion / Q000473:pathology; D012171:Retinal Vessels / Q000473:pathology*; D060388:Support Vector Machine